The paradox of productivity during quarantine: an agent-based simulation

Life and self-organization on the way to artificial intelligence for collective dynamics

This work is dedicated to the study, modeling, and simulation, of the collective dynamics of interacting living entities. The first perspective is to develop a mathematical theory of swarm intelligence for the above mentioned systems. The second perspective is to design the conceptual tools for a theory of artificial intelligence. The aim is to model a dynamics where interacting entities learn from other entities as well as from the environment and external actions. Then, out of this collective learning process, each entity develops a strategy to pursue specific goals through a decision making process that leads to the dynamic. The approach is based on developments of the kinetic theory of active particles. This paper does not naively state that the problem of artificial intelligence for collective dynamics has been exhaustively considered, but some hints are proposed to contribute to such a challenging perspective in view of further developments.

What is life? Active particles tools towards behavioral dynamics in social-biology and economics

This review paper is devoted to study the conceptual difficulties that mathematics meets when attempting to describe the complexity of living matter focusing on the challenging perspective of developing a mathematical theory for living systems including mutations and selection. The quest starts with the identification of a number of common complexity features of living systems. Then, mathematical structures are derived to include these features, while mathematical models are derived by inserting in the structures models of individual based interactions. Three applications are examined by active particles methods, i.e., models of SARS2-CoV-2 pandemics, models of idiosyncratic learning in open markets and of the dynamics of prices accounting for human behaviors. A critical study, which pervades the whole paper, shows that also economics can be viewed as a behavioral science thus accounting for specific aspects typical of living systems.

Working in the digital economy: A systematic review of the impact of work from home arrangements on personal and organizational performance and productivity

Work-from-home has become an increasingly adopted practice globally. Given the emergence of the COVID-19 pandemic, such arrangements have risen substantially in a short timeframe. Work-from-home has been associated with several physical and mental health outcomes. This relationship has been supported by previous research; however, these health and safety issues often receive little resources and attention from business perspectives compared to organizational and worker performance and productivity. Therefore, aligning work-from-home practices with business goals may help catalyze awareness from decision makers and serve to effectively implement work-from-home policies. We conducted a review to synthesize current knowledge on the impact of work-from-home arrangements on personal and organizational performance and productivity. Four large databases including Scopus, PubMed, PsychInfo, and Business Source Complete were systematically searched. Through a two-step screening process, we selected and extracted data from 37 relevant articles. Key search terms surrounded two core concepts: work-from-home and productivity/performance. Of the articles published prior to the COVID-19 pandemic, 79% (n = 19) demonstrated that work-from-home increased productivity and performance whereas 21% (n = 5) showed mixed or no effects. Of the articles published during the pandemic, 23% (n = 3) showed positive effects, 38% (n = 5) revealed mixed results, and 38% (n = 5) showed negative effects. Findings suggest that non-mandatory work-from-home arrangements can have positive impacts on productivity and performance. When work-from-home becomes mandatory and full-time, or external factors (i.e., COVID-19 pandemic) are at play, the overall impacts are less positive and can be detrimental to productivity and performance. Results will help foster an understanding of the impact of work-from-home on productivity and performance and inform the development of organizational strategies to create an effective, resilient, and inclusive work-from-home workplace by helping to effectively implement work-from-home policies that are aligned with business goals.

Pandemics of mutating virus and society: a multi-scale active particles approach

This article presents, within a multiscale framework, a search for a unified approach towards modelling the COVID-19 pandemic, from contagion to within-host dynamics. The modelling is focused on vaccination and therapeutical actions in general. The first part of our article is devoted to understanding the complex features of the system and to the design of a modelling rationale. Then, the modelling approach follows mainly focused on the competition between the proliferating virus and the immune system. Modelling considers also the action of vaccination plans related to the onset of new variants. This article is part of the theme issue 'Kinetic exchange models of societies and economies'.

A stochastic model for the influence of social distancing on loneliness

The short-term economic consequences of the critical measures employed to curb the transmission of Covid-19 are all too familiar, but the consequences of isolation and loneliness resulting from those measures on the mental well-being of the population and their ensuing long-term economic effects are largely unknown. Here we offer a stochastic agent-based model to investigate social restriction measures in a community where the feelings of loneliness of the agents dwindle when they are socializing and grow when they are alone. In addition, the intensity of those feelings, which are measured by a real variable that we term degree of loneliness, determines whether the agent will seek social contact or not. We find that decrease of the number, quality or duration of social contacts lead the community to enter a regime of burnout in which the degree of loneliness diverges, although the number of lonely agents at a given moment amounts to only a fraction of the total population. This regime of mental breakdown is separated from the healthy regime, where the degree of loneliness is finite, by a continuous phase transition. We show that the community dynamics is described extremely well by a simple mean-field theory so our conclusions can be easily verified for different scenarios and parameter settings. The appearance of the burnout regime illustrates neatly the side effects of social distancing, which give to many of us the choice between physical infection and mental breakdown.